Grok 4.5
grok-4-5
70% in · 30% out mix
Higher = better value
Speed
89/100
Context
500K
Tier
smart
GPT-4.1
gpt-4-1
70% in · 30% out mix
Higher = better value
Speed
88/100
Context
1.0M
Tier
smart
IN-DEPTH ANALYSIS
Grok 4.5 vs GPT-4.1: Detailed Comparison
Grok 4.5 is xAI's mid-range-tier language model with a 500K-token context window, excelling at reasoning. GPT-4.1 from OpenAI is a mid-range-tier model supporting 1.0M tokens in context, with standout performance in reasoning.
This is a genuine tradeoff rather than a clear win. GPT-4.1 leads by 5 points on combined coding and reasoning, and charges 16% more per blended million tokens to do it. The margin is narrow enough that the answer depends on your workload: on tasks where the extra capability shows up, the premium pays for itself; on routine work it does not. Grok 4.5 is priced at $2.00/M input tokens and $6.00/M output tokens. GPT-4.1 costs $2.00/M input and $8.00/M output.
In independent benchmark evaluations, GPT-4.1 leads with coding scores of 91/100 and reasoning scores of 93/100, compared to Grok 4.5's 89/100 in coding and 90/100 in reasoning.
Capability breakdown
Across the five core benchmark categories, here is how Grok 4.5 and GPT-4.1 stack up head to head:
Best model by task
- coding: GPT-4.1 wins with 91/100
- reasoning: GPT-4.1 wins with 93/100
- data extraction: GPT-4.1 wins with 92/100
- creative tasks: GPT-4.1 wins with 90/100
- vision/multimodal: GPT-4.1 wins with 91/100
Estimated monthly cost at scale
At 10M + 2M per month, Grok 4.5 runs about $32.00 while GPT-4.1 runs about $36.00 — Grok 4.5 saves roughly $4.00 (11%) every month.
What actually decides it
Grok 4.5 and GPT-4.1 come from different labs, which means different tokenizers, different API shapes, and a second vendor relationship. The same English text does not produce the same token count on both, so a price-per-million comparison understates the difference — measure your own prompts on each before treating the headline rates as the full story.
Grok 4.5 and GPT-4.1 are 15 months apart, which is more than one generation in this market. Benchmark comparisons across that gap flatter the older model: it was measured against the evaluations that existed at the time. Treat GPT-4.1's scores as a floor for what it does well and be sceptical of a close-looking result.
GPT-4.1 carries the larger context window at 1.0M tokens versus 500K for Grok 4.5. The gap is real but not decisive — it matters if your prompts routinely run long, and is irrelevant if they sit where most production prompts sit, well under 100K. Bear in mind that filling a large window is also what makes a request expensive.
Throughput is close enough to ignore — 89/100 versus 88/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
One practical asymmetry: GPT-4.1 offers a batch API at 50% off standard rates, and Grok 4.5 does not. For anything that does not need an answer immediately — nightly enrichment, backfills, evaluation runs — that discount can be worth more than the difference in list price, and it is easy to overlook when comparing headline rates.
Neither model is the obvious answer. GPT-4.1 leads on benchmarks, Grok 4.5 on cost, and the gap is small on both. Run the calculator above with your real token mix — for most workloads that decides it faster than any benchmark table will.
Benchmark Comparison
Head-to-head scores across 5 categories — sourced from official evals
Coding
Reasoning
Extraction
Creative
Vision
Speed Score
Context Window
What Is a Token?
Models don't read words — they process tokens.
A token is roughly 4 characters of English text (~¾ of a word). Your API bill is priced per million tokens — understanding this directly reduces your costs.
Short phrase
"Hello, world!"
- Grok 4.5
- $0.80
- GPT-4.1
- $0.80
Business email
One typical email (~200 words)
- Grok 4.5
- $54.00
- GPT-4.1
- $54.00
Code file
50-line Python script
- Grok 4.5
- $80.00
- GPT-4.1
- $80.00
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both Grok 4.5 and GPT-4.1, so the number only becomes meaningful at production volume. Input tokens only; add your output volume in the calculator below.
How to check your token usage
response.usage.total_tokensEvery API response includes a usage object. Sum total_tokens across all calls to get your monthly figure, then use the calculator below.
Your Cost Calculator
Enter your actual monthly token usage to see real savings
Quick Presets
Grok 4.5
$96.00/mo
$1,152.00/yr
GPT-4.1
$114.00/mo
$1,368.00/yr
Annual Savings
$216.00 saved per year
Grok 4.5 cheaper · $18.00/mo
Deep-Dive Audit — Grok 4.5 & GPT-4.1
Surgically Auditing: Deep Logic
3-YEAR STRATEGIC LOSS PROJECTION
$199.404
Without optimization protocols, current model choices will result in $66.468 capital loss per year.
EFFICIENCY SCORE
90%
This model achieves a 90 benchmark score in this category.
CATEGORY GAP
10 pts
Distance from Leader
Competitive Landscape Analysis
Source: MMLU-Pro + GPQA Diamond (Apr 2026)
Category Champion: Claude Fable 5
According to MMLU-Pro + GPQA Diamond (Apr 2026) data, Claude Fable 5 provides the optimum balance for Deep Logic tasks.
Market Score
%100
Savings Rate
%69
Operational Prescription
- Implement model cascading to optimize token spend.
- Analyze complex_reasoning data to leverage local semantic caching.
COST AUDIT PROTOCOL
Overkill Detected
"Grok 4.5 is overpriced for this task type. Claude Fable 5 scores 100 in this category at a fraction of the cost."
Categorical Alternative Opportunity
"Claude Fable 5 leads this category with 100 points according to MMLU-Pro + GPQA Diamond (Apr 2026) data."
Inertia Tax Detected
"85% of traffic can be routed to cheaper models. Fast tier (GPT-5 Nano) and Smart tier (o3-mini) can save $5.54/month."
3-Tier Intelligent Routing Architecture
69% SAVINGS VIA ROUTINGGPT-5 Nano
IQ Score: 72/100
$18.00/yr
o3-mini
IQ Score: 97/100
$277.20/yr
DeepSeek R1
IQ Score: 97/100
$59.184/yr
Without tiered routing, you pay the 'Inertia Tax' — routing all traffic to the most expensive model regardless of task complexity. Tiered cascade eliminates $797.616/year in avoidable overhead.
Deep Logic — Model Cost / Quality Matrix
Source: MMLU-Pro + GPQA Diamond (Apr 2026)| Model | Benchmark | Input (per M) | Output (per M) | Annual Cost* | Value Index |
|---|---|---|---|---|---|
o3-miniBEST VALUE | 97/100 | $1.10 | $4.40 | $66.00 | 100/100 |
GPT-5.2 Chat | 96/100 | $1.75 | $14.00 | $189.00 | 35/100 |
Claude 3.7 Sonnet | 95/100 | $3.00 | $15.00 | $216.00 | 30/100 |
GPT-5.6 Terra | 94/100 | $2.00 | $12.00 | $168.00 | 38/100 |
Claude 3.5 Sonnet | 93/100 | $3.00 | $15.00 | $216.00 | 29/100 |
GPT-4.1 | 93/100 | $2.00 | $8.00 | $120.00 | 53/100 |
Claude Sonnet 5 | 92/100 | $3.00 | $15.00 | $216.00 | 29/100 |
Grok 4.5SELECTED | 90/100 | $2.00 | $6.00 | $96.00 | 64/100 |
GPT-4o | 90/100 | $2.50 | $10.00 | $150.00 | 41/100 |
Gemini 3.1 Pro | 89/100 | $2.00 | $12.00 | $168.00 | 36/100 |
Gemini 2.0 Pro | 88/100 | $1.25 | $5.00 | $75.00 | 80/100 |
Gemini 1.5 Pro | 87/100 | $1.25 | $5.00 | $75.00 | 79/100 |
Mistral Large 2 | 86/100 | $2.00 | $6.00 | $96.00 | 61/100 |
* Annual cost for given volumes. Value Index = Score / Cost (Higher = Best Value).
// iOPTERA Surgical Routing Wrapper
const auditModel = async (prompt: string) => {
const complexity = measureComplexity(prompt);
// Tactical Cascade Logic
if (complexity < 0.45) {
// Redirect simple tasks to efficient model
return await llm.call("iOPTERA Optimization", prompt);
}
// High-latency routing for complex reasoning
return await llm.call("Claude Fable 5", prompt);
};Related Comparisons
Explore similar model pairs to find your best fit